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lte-cnn's Introduction

This contains code to apply deep CNN networks for LTE signal classification

Basic Info:

train_model.py is the main file for training the model.

core/ contains the code to introduce CNN layers
All data needs to be stored in folder data/

Before running create a folder to save checkpoints in and provide it as input

Sample Command:

python train_model.py -d lte_tdwaveform.csv -dL train_lbl.csv -v lte_tdwaveform_val.csv -t lte_tdwaveform_test.csv -tL test_lbl.csv -vL val_lbl.csv

Dependencies: 1. Python 2.7 distribution with numpy - Ideally use anaconda2

2. Theano
   - gcc
   - blas
   - CUDA (optional)
   - Follow instruction here for simple cpu install on windows
        http://stackoverflow.com/questions/33687103/how-to-install-theano-on-anaconda-python-2-7-x64-on-windows
   - Instructions here for adding blas and gpu support
        https://github.com/Lasagne/Lasagne/wiki/From-Zero-to-Lasagne
        http://computerscienceunveiled.blogspot.in/2015/08/installing-openblas-for-theano-on.html

3. Keras
   - simple 'pip install keras'

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